Affinity Diagram

1
Affinity Diagram

• What is it?
• Organized output from brainstorming session.
• A tool to generate, organize, and consolidate
  information.
• A tool that helps an improvement team to develop
  its own system of thought concerning an issue.

2
Affinity Diagram

• When is it used?
• Answer yes to the following
• Is the problem (or issue) complex and hard to
  understand?
• Is the problem uncertain, disorganized, or
  overwhelming?
• Does the problem require the involvement and
  support of a group?

3
Affinity Diagram

• How is it made?
• Choose a group leader.
• State the issue or problem.
• Brainstorm and record ideas.
• Move the cards into like piles.
• Name each group with a header card.
• Draw the affinity diagram.
• Discuss the piles.

4
Affinity Diagram

• Remember
• Helps a team analyze a complex problem.
• Can further analyze by making a relations diagram.

5
Affinity Diagram

• Getting the most
• Use with other planning tools such as a relations
  diagram.
• Helps identify the area that may be most
  important.
• Use to break old thought pattern.

6
Attributes Charts

• What are they?
• Control charts used to monitor attributes data.
• Data is counted, not measured.
• Data is collected on certain characteristics that
  have been operationally defined.

7
Attributes Charts

• What kinds are there?
• Nonconforming - Ex failing students
• np - number of sample failures.
• p - proportion of sample failures.
• Nonconformities - Ex discipline problems
• c - number of occurrences per subgroup
• u - number of occurrences per unit.

8
np Control Chart

• What is it?
• An attributes control chart that shows how a
  system changes over time.
• Measured by the number of nonconforming items
  produced.
• Helps minimize changes of overcontrol or
  undercontrol.
• Used to assess stability and monitor improvement.

9
np Control Chart

• When is it used?
• Answer yes to all of the following
• 1. Do you need to assess system stability?
• 2. Is the data the number of noncomforming
  items per subgroup.
• 3. Are all subgroups the same size?
• 4. Can there be only two outcomes to any given
  check?
• 5. Has the characteristic been operationally
  defined prior to data collection?
• 6. Is the time order of subgroups preserved?

10
np Control Chart

• How is it made?
• 1. Complete the header information.
• 2. Record the data.
• 3. Calculate the average number (np).
• 4. Calculate the control limits.
• 5. Determine the scaling for the chart.
• 6. Draw the center line and control limits.
• 7. Plot the values on the chart.
• 8. Interpret the control chart.

11
np Control Chart

• Remember
• It records the number of nonconforming items per
  subgroup
• The subgroups must all be the same size.
• The characteristic being charted must be
  operationally defined prior to data collection.

12
np Control Chart

• Getting the most
• Use control charts for different
• purposes
• Assess system stability.
• As a tool to stratify data.
• Assess improvement theories.
• Interpret the data.
• Monitor the data following
• standardization.

13
np Control Chart

• What is it?
• An attributes control chart that shows how a
  system changes over time.
• Measured by the proportion of nonconforming items
  produced.
• A tool to help minimize the chance of overcontrol
  or undercontrol.
• Used to assess stability and monitor improvement.

14
p Control Chart

• When is it used?
• Answer yes to the following
• 1. Do you need to assess system stability?
• 2. Is the data composed of counts that can be
  converted to proportions?
• 3. Can there be only two outcomes to any given
  check?
• 4. Has the characteristic being charted been
  operationally defined prior to data collection?
• 5. Is the time order of subgroups preserved?

15
p Control Chart

• How is it made?
• 1. Complete the header information.
• 2. Record the data.
• 3. Calculate the proportion for each
  subgroup.
• 4. Calculate the average proportion (p).
• 5. Calculate the control limits.
• a. Calculate the average subgroup size
• (n).
• b. Determine the subgroup size limits.

16
p Control Chart

• How is it made? (cont.)
• 5. Calculate the control limits (cont.)
• c. Calculate the control limits for all the
  data.
• d. Calculate the control limits for
  subgroups that vary excessively.
• 6. Determine the scaling for the chart.
• 7. Draw the center line and control limits.
• 8. Plot the values on the chart.
• 9. Interpret the control chart.

17
p Control Chart

• Remember
• It records the proportion of nonconforming items
  per subgroup.
• The subgroup size can vary.
• The characteristic being charted must be
  operationally defined prior to data collection.

18
p Control Chart

• Getting the most
• Use control charts for different purposes
• Assess system stability.
• As a tool to stratify data.
• Assess improvement theories.
• Interpretation of the data.
• Monitoring the data following standardization.

19
p Control Chart

• What is it?
• An attributes control chart that shows how a
  system changes over time.
• Measured by the number of nonconformities per
  subgroup produced.
• A tool to help minimize the chance of overcontrol
  or undercontrol.
• Used to assess stability and monitor improvement.

20
c Control Chart

• When is it used?
• Answer yes to all of the following
• 1. Do you need to assess system stability?
• 2. Is the data the number of nonconformities
  per
• subgroup.
• 3. Is the subgroup size the same for all
• subgroups?
• 4. Have the possible nonconformities been
• operationally defined prior to data
  collection?
• 5. Is the time order of subgroups preserved?

21
c Control Chart

• How is it made?
• Complete the header information.
• Record the data.
• Calculate the average number ( c ).
• Calculate the control limits.
• Determine the scaling for the chart.
• Draw the center line and control limits.
• Plot the values on the chart.
• Interpret the control chart.

22
c Control Chart

• Remember
• A c-chart records the number of nonconformities
  per subgroup.
• The characteristics being counted must be
  operationally defined before data collection
  begins.
• The subgroup size must remain the same for all
  subgroups.

23
c Control Chart

• Getting the most
• Use control charts for different purposes
• Assess system stability.
• As a tool to stratify data.
• Asses improvement theories.
• Interpret the data.
• Monitor the data following
• standardization.

24
u Control Chart

• What is it?
• An attributes control chart that shows how a
  system changes over time.
• Measured by the number of nonconformities per
  subgroup produced.
• A tool to help minimize the chance of overcontrol
  or undercontrol.
• Used to assess stability and monitor improvement.

25
u Control Chart

• When is it used?
• Answer yes to all of the following
• 1. Do you need to assess system stability?
• 2. Is the data the number of
• nonconformities per subgroup?
• 3. Have the possible nonconformities been
  operationally
  defined prior to data collection?
• 4. Is the time order of subgroups preserved?

26
u Control Chart

• How is it made?
• 1. Complete the header information.
• 2. Record the data.
• 3. Calculate the number of nonconformities per
  unit (u) for each subgroup.
• 4. Calculate the average number (u).
• 5. Calculate the control limits.
• a. Calculate the average subgroup size
  (n).
• b. Determine the subgroup size limits.

27
u Control Chart

• How is it made? (cont.)
• 5. Calculate the control limits (cont.)
• c. Calculate the control limits for all data.
• d. Calculate the control limits for subgroups
  that vary excessively
• 6. Determine the scaling for the chart.
• 7. Draw the center line and control limits.
• 8. Plot the values on the chart.
• 9. Interpret the control chart.

28
u Control Chart

• Remember
• A u-chart records the number of nonconformities
  per subgroup.
• The characteristics being counted must be
  operationally defined before data collection
  begins.
• The subgroup size can vary.

29
u Control Chart

• Getting the most
• Use control charts for different purposes
• Assess system stability.
• As a tool to stratify data.
• Assess improvement theories.
• Interpret the data.
• Monitor the data following standardization.

30
Brainstorming

• What is it?
• The free, uninhibited generation of ideas,
  usually in a group setting.
• A process for generating many ideas through group
  dynamics.
• A tool used by improvement teams in many
  different settings when working on a project.

31
Brainstorming

• When is it used?
• To solicit ideas from a group on a given topic
  such as project selection or problem causes.
• To generate improvement actions.

32
Brainstorming

• Goals
• To generate a wide variety and extensive number
  of ideas.
• Everyone on the team becomes involved in the
  problem solving process.
• To insure that nothing is overlooked.
• To create an atmosphere of creativity and
  openness.

33
Brainstorming

• Rules
• No criticism allowed.
• Each person has an equal opportunity to express
  ideas.
• Quantity over quality.
• Piggybacking or hitchhiking is encouraged.

34
Brainstorming

• How is it made?
• 1. Select a recorder and group facilitator.
• 2. Generate ideas.
• 3. Record the ideas.
• 4. (Optional) Organize results using
  Affinity or C E Diagrams or Nominal Group
  Technique.

35
Cause Effect Diagram

• What is it?
• A picture of various system elements that may
  contribute to the problem.
• Helps to identify possible causes of a specified
  problem (or effect).
• Useful in manufacturing, service, and
  administrative applications.
• Used by an improvement team to find special and
  common causes of variation and to analyze causes.
• Also called Ishikawa Diagram or Fishbone Diagram.

36
Cause Effect Diagram

• When is it used?
• Answer yes to one or both of these questions
• 1. Do root causes of a problem need to be
  identified?
• 2. Are there ideas and/or opinions about the
  causes of a problem?

37
Cause Effect Diagram

• How is it made?
• 1. Identify the problem.
• 2. Record the problem statement.
• 3. Draw and label the main bones.
• 4. Brainstorm for problem causes.
• 5. Identify the most likely cause
  candidates.

38
Cause Effect Diagram

• Remember
• A graphic way to display a lot of cause
  information in a compact space
• Helps teams move from opinions to theories that
  can be tested
• Is critical to understanding how to improve
  systems
• May be difficult to make

39
Cause Effect Diagram

• Getting the most
• Once causes have been selected from the diagram
• verify that causes produce the effect expected
• Verify that the effect is not produced in the
  absence of these causes
• Can be done at multiple levels in search of root
  cause

40
Cause Effect Diagram

• Variations
• Process Analysis C E Diagram
• Negative C E Diagram

41
Control Chart Interpretation

• What is it?
• The process of analyzing the chart to understand
  the performance of the system being studied
• A way to help people who are managing systems
  make the right decisions about how to control and
  run them
• A tool to help minimize the chance of making two
  mistakes when working on a system overcontrol or
  undercontrol

42
Control Chart Interpretation

• When is it used?
• Interpret every chart
• Re-interpret with every new point

43
Control Chart Interpretation

• How to interpret control charts
• 1. Look for unstable conditions
• - Any point outside control limits
• - Run of seven points
• - Nonrandom patterns
• 2. Declare the system in control (stable) or
  out of control (unstable)
• 3. Respond to the information on the chart.

44
Control Chart Interpretation

• Remember
• - Interpret charts after calculating control
  limits.
• - It is a way of reading signals in charts.
• - It is a mental process of questions and
  pattern
• recognition
• - Out of control does not always mean trouble.
• - Basic rules for recognizing unstable
  conditions.
• - Any point outside control limits.
• - Run of seven points.
• - Nonrandom patterns.

45
Control Chart Interpretation

• Getting the most
• Variables charts
• - Central location and variability
• - Variability first
• - X-MR points are not averages or medians
• Attributes charts
• - Note direction of point movement
• - Interpret p- and u-charts with variable
• limits in usual way

46
Control Chart Interpretation

• Getting the Most(cont.)
• Advanced rules
• - Trends
• - Clusters
• - Sawtooth
• - Two of three beyond 2-sigma
• - Four of five beyond 1-sigma

47
Check Sheet

• What is it?
• - A tool for collecting data in a consistent
  
• form.
• - Provides an easy, structured way of
• recording data as it is collected
• - Assures data will be recorded in similar
• manner

48
Check Sheet

• What is it? (cont.)
• - Formats can be designed for various needs
• - Most commonly arranged in columns or
• matrix
• - Used by improvement teams to gather data

49
Check Sheet

• When is it used?
• Answer yes to all of the following
• 1. Is data to be collected?
• 2. Is an organized format for collecting data
  needed.
• 3. Will different people be collecting or
  using the data for study or project?

50

• How is it made?
• 1. List the data needs.
• 2. Decide on format.
• 3. Design and produce form.
• 4. Review design.
• 5. Test the form.

51
Check Sheet

• Remember
• - A check sheet provides a format for
• collecting data
• - A good design increases the efficiency of
• data use.
• - The check sheet is designed to make data
• gathering and analysis easier.
• - There are unlimited format designs.

52
Flow Chart

• What is it?
• - A picture of any process
• - Drawn with standard symbols
  representing different types of activities
• - Style and depth chosen should be
• consistent and useful
• - Different styles available, 2 covered
• - Deployment
• - Process

53
Flow Chart

• Purpose
• - Defines the system being studied
• - Gets agreement
• - Identifies value added activities
• - Identifies dead wood activities
• - Identifies areas of data stratification
• - Documents changes to the process

54
Deployment Flow Chart

• When is it used?
• Answer yes to all of the following
• 1. Is a picture of the process needed?
• 2. Is it necessary to show the
  relationship of the people and process
  steps?
• 3. Will the process be pictured as it
  actually operates?

55
Deployment Flow Chart

• How is it made?
• 1. Define the process boundaries.
• 2. Observe the process in operation.
• 3. Draw a People Coordinate.
• 4. List major steps in the process.
• 5. Draw the flow chart, using symbols
• 6. Study the flow chart.

56
Flow Chart

• Remember
• - A flow chart is a picture of a process.
• - Choosing the style and depth of detail
  
• depends on purpose.
• - Everyone involved with the process
• should help in construction and agree on
• picture.
• - A flow chart is a dynamic tool which
• should be changed when process changes
• are made.

57
Flow Chart

• Getting the most
• - Use them on an ongoing basis expand
• into more detail.
• - Keep them current, as they should
• represent the current, best known way to
• operate.

58
Process Flow Chart

• What is it?
• - A picture of the major steps in a process
• - Does not show the relationship of the
  
• people doing the work and the steps in
• the process

59
Process Flow Chart

• When is it used?
• Answer yes to all of the following
• 1. Is a picture of a process needed?
• 2. Are actual steps in the process shown?
• 3. Is it unnecessary to show the
• relationship between the people doing
  the work and the work being done?

60
Process Flow Chart

• How is it made?
• 1. Observe the process.
• 2. List all steps in the process.
• 3. Arrange the steps in sequence.
• 4. Draw the Flow Chart.
• 5. Study the Flow Chart.

61
Force Field Analysis

• What is it?
• A problem-solving tool to help change occur
• Views change as a struggle between forces -
  Driving forces help change occur
• - Restraining forces block the change

62
Force Field Analysis

• When is it used?
• - Any time a change is expected to be
• difficult

63
Force Field Analysis

• How is it made?
• 1. Define the desired change or action.
• 2. Brainstorm the driving forces.
• 3. Brainstorm the restraining forces.
• 4. Prioritize the driving forces.
• 5. Prioritize the restraining forces.
• 6. List action to be taken.

64
Force Field Analysis

• Remember
• Reviews proposed change from both for and against
  viewpoint.
• Provides a starting point for action.
• A list of actions is the output.

65
Force Field Analysis

• Variations
• Match forces
• Driving forces and restraining forces are matched
  in an attempt to cancel each other out
• If no match exists for restraining force(s),
  action will be developed to reduce, eliminate, or
  reverse

66
Histogram

• What is it?
• - Bar graph of raw data
• - A tool to show central location, shape, and
• spread of data
• - A means to gain knowledge about the
• system
• - A way to assess stability so that
• predictions about system performance can
• be made.

67
Histogram

• When is it used?
• Answer yes to all of the following
• 1. Do you have a data set of related values?
• 2. Is it important to visualize central
  location, shape, and spread of the data?

68
Histogram

• How is it made?
• 1. Select the classes.
• a. Determine the number of classes.
• b. Determine the class width and
• boundaries
• 2. Record the data.
• 3. Prepare the axes.
• b. Draw and label the horizontal and
• vertical axes.
• b. Scale and label each axis.

69
Histogram

• How is it made? (cont.)
• 4. Draw the histogram.
• 5. Study the shape.
• 6. Calculate the statistics.
• A. Central location.
• B. Spread
• 7. Compare your histogram to the normal
• distribution.

70
Histogram

• Remember
• Is a picture of a set of data
• Can use to make predictions about the future if
  the system is stable
• Shows central location, shape and spread

71
Histogram

• Getting the most
• Apply the concepts of central location, shape,
  and spread.
• Use to predict when the system is stable.

72
Measurement Examples

• Function Is the system doing what it is
  supposed to do?
• - Performance, of students who master
• first time, rework, errors
• Cost What are the costs to the customers,
  either internal or external?
• - Unit cost, losses, material costs (non)quality
  
• costs, loss of self-esteem, length of time
  it takes
• for a teacher to use a new teaching method

73
Measurement Examples

• (cont.)
• Delivery Is the product or service there when
  and where the customer needs it?
• - On-time, where needed, quantity needed,
• inventory, lead time, cycle time, cause
• availability

74
Measurement Examples

• (cont.)
• Safety Is the product or service physically and
  psychologically safe for the user?
• - Survey results, anecdotal information,
• critical incident reports
• Morale Are the internal customers satisfied?
• - Survey results, anecdotal information,
• critical incident reports

75
Nominal Group Technique

• What is it?
• - A structured group process used to help
• make decisions
• - A tool to give everyone on the team an
• equal voice in decision making
• - A way to generate more unique, higher
• quality ideas

76
Nominal Group Technique

• When is it used?
• When you need to generate and choose a course of
  action for improvement

77
Nominal Group Technique

• How is it made?
• 1. State the defined area of opportunity
• 2. Silently generate action items
• 3. State and record the ideas
• 4. Discuss each item on the list
• 5. Establish criteria for the voting

78
Nominal Group Technique

• How is it made? (cont.)
• 6. Conduct a preliminary vote.
• a. Individuals choose the items most
• important to them.
• b. Rank order the cards.
• c. Record the votes.
• d. Discuss the results of the vote.

79
Nominal Group Technique

• Remember
• - Helps to generate and choose actions
• - Minimizes internal group influences
• - Promotes team commitment to actions by
• involving all members in decision making

80
Nominal Group Technique

• Getting the most
• - Use for planning continuous improvement.
• - Use over time.

81
Nominal Group Technique

• Variations
• - Decision matrix

82
Operational Definition

• What is it?
• - Gives a clear, concise, and detailed
  definition of a measure
• - Provides clear communication among everyone in
  the system
• - Yields a single yes or no answer, is
  consistently applied, and is understandable
• - Defines measures for improvement teams before
  they begin gathering data

83
Operational Definition

• Attributes data
• - Data that is counted
• - number of absent students
• - number of missed homework items
• - number of tardies
• - The operational definition is fundamental to
  improve uniformity of judgement.

84
Operational Definition

• Attributes data
• - Data that is counted
• - number of absent students
• - number of missed homework items
• - number of tardies
• - The operational definition is fundamental
• to improve uniformity of judgement

85
Operational Definition

• (cont.)
• Variables data
• - Data that is measured
• - time
• - money
• - electricity usage
• - The operational definition gives specific
• instruction on how criteria is measured.

86
Operational Definition

• What does it look like?
• 1. Characteristic of interest
• - Purchase delivery time.
• 2. Measuring instrument
• - A calendar and the holiday schedule.

87
Operational Definition

• What does it look like? (cont.)
• 3. Method of test
• - Three campuses and one support site will be
  included in the sample for the months of
  September-April (1991-92). Requisition will be
  selected randomly (every 10th requisition does
  not have a P.O., then select the next requisition
  for which a P.O. was issued). The desired data
  is the number of working days between issuance of
  the requisition by a site and the date the
  completed purchase order is received at the site.
  This number is determined by subtracting the
  requisition date and then subtracting the number
  of non-working days and holidays during that
  period.

88
Operational Definition

• What does it look like? (cont.)
• 4. Decision criteria
• - The number of working days required
• from requisition to delivery of
• materials at the site.

89
Operational Definition

• When is it used?
• - With every project when defining quality
• measures

90
Operational Definition

• How is it made?
• 1. Identify the characteristic of interest.
• 2. Select measuring instrument.
• 3. Describe the test method.
• 4. State the decision criteria.
• 5. Document the operational definition.

91
Operational Definition

• Remember
• - Helps reduce the variability in data
  collection
• - Is required for both attributed and variables
• data
• - Is used by improvement teams to define
• quality measures before gathering data

92
Operational Definition

• Getting the most
• - Check the operational definition and
• evaluation whenever system is unstable
• - Use as a communication tool between
• customer and supplier.
• - Test the operational definition before
• standardizing by applying the method of
• test.

93
Pareto Diagram

• What is it?
• - A bar chart which ranks related measures
  
• in decreasing order of occurrence
• - A tool to separate the significant aspects
• from the trivial ones
• - A way to stratify data, study improvement
• results, and plan for continuous
• improvement

94
Pareto Diagram

• When is it used?
• - Answer yes to all of the following
• 1. Can data be arranged in categories?
• 2. Is the rank of each category
• important?

95
Pareto Diagram

• How is it made?
• 1. Select logical categories.
• 2. Specify the time period.
• 3. Collect the data.
• 4. Construct a frequency table.
• 5. Draw and scale the horizontal and
• vertical axes.
• a. Draw the horizontal axis.
• b. Decide on the scaling floor.

96
Pareto Diagram

• How is it made? (cont.)
• 5. Draw and scale the horizontal and
• vertical axes. (cont.)
• c. Draw the vertical axis.
• d. Scale the vertical axis.
• 6. Draw and label the bars for each
• category
• 7. Draw the cumulative percentage line.
• 8. Review the results of the Pareto.

97
Pareto Diagram

• Remember
• - A pareto diagram is a bar chart that ranks
• data by categories
• - It is based on the idea that only a few
• categories contain most of the data.
• - The largest bar(s) directs team efforts.
• - Team can use tool for several purposes during
• the project.
• - Pareto is a simple, powerful tool.

98
Pareto Diagram

• Getting the most
• - Use subdivisions when the data is first
• collected at the general level.
• - Use multi-perspective analysis when the
• data can be stratified.
• - Repeat analysis to see how the system is
• changing.
• - Study the systems stability before doing
• Pareto analysis.

99
Relations Diagram

• What is it?
• - A picture of cause-and-effect relationships
• between elements of a problem
• - Management tool to help identify root
• causes and root effects of a problem

100
Relations Diagram

• When is it used?
• Answer yes to all of the following
• 1. Do the aspects of a complex issue
• need to be analyzed and understood?
• 2. Is the team having trouble getting to
• the root causes of a problem because
  only symptoms seem to be apparent?

101
Relations Diagram

• How is it made?
• 1. Clearly define the issue or problem.
• 2. Construct the diagram layout.
• 3. Analyze the relationships.
• 4. Count the arrows.
• 5. Identify the root causes and effects.
• 6. Study the final diagram.

102
Relations Diagram

• Remember
• - Helps analyze cause-and-effect
• relationships among elements of a
• problem
• - Directs a team toward the root causes of a
• problem

103
Relations Diagram

• Getting the most
• - Use over time and revisit the diagram to
• check teams progress.

104
Run Chart

• What is it?
• - A line graph of data plotted over time
• - Data can be attributes or variables
• - A means of looking at the systems
• behavior over time
• - A tool used by an improvement team
• when gathering baseline data at the
• beginning of a project

105
Run Chart

• When is it used?
• Answer yes to all of the following
• 1. Is the data collected over time?
• 2. Is the time order of the data preserved?

106
Run Chart

• How is it made?
• 1. Complete the header information.
• 2. Record the data.
• 3. Determine the scaling for the chart.
• 4. Plot the values on the chart.
• 5. Interpret the chart.

107
Run Chart

• Remember
• - A plot of data over time
• - Time is plotted on horizontal axis, variable
• value on vertical axis.
• - Used to detect trends or patterns in data
• over time
• - The basis for a control chart

108
Run Chart

• Getting the most
• - Use often and with different kinds of data
• - Display of public
• - Use as a quick test of system performance

109
Sampling

• What is it?
• - The process of selecting the size and
• frequency of samples being taken from a
• subgroup
• - The process of selecting a representative
• part of a population to estimate
• characteristics of the population
• - A process of gathering data at a lower cost
• without reduced accuracy

110
Sampling

• Terms
• - Population
• - The area under study
• - Frame
• - A listing of all the elements in the
  population
• - Sample
• - The actual data gathered for quantitative
• analysis, also called subgroups
• - Conceptual Population
• - The past, current, and future population
• - Assumes that the process is ongoing

111
Sampling

• When is it used?
• Any time data is to be gathered

112
Sampling

• How is it made?
• 1. Determine what question you are
• thinking of the data.
• 2. Determine the frequency of sampling.
• 3. Determine the actual frequency times.
• 4. Select the subgroup size.
• a. Variables data
• b. Attributes data

113
Sampling

• Remember
• Guided the quantitative study of a system
• Is used to minimize cost and improve accuracy
• Frequency depends on how often a process changes

114
Scatter Diagram

• What is it?
• A graph showing the plotted values of two factors
• A tool demonstrating whether or not two factors
  are related

115
Scatter Diagram

• When is it used?
• Answer yes to all of the following
• 1. Do you want to test whether the
• performance of one factor is related to
• the performance of another?
• 2. Are the two factors
• a. A quality characteristic and a factor
  you suspect affects it, OR
• b. Two related quality characteristics,
• OR
• c. Two factors suspected of relating to
• the same quality characteristics.

116
Scatter Diagram

• How is it made?
• 1. Draw and label the horizontal and vertical
  axes.
• 2. Scale each axis.
• 3. Plot the points.
• 4. Interpret the scatter diagram
• a. Look for patterns.
• b. Look for outliers.

117
Scatter Diagram

• Remember
• Can be constructed if a relationship is thought
  to exist between two factors
• Is used to verify causes
• The pattern, if any, gives information about how
  the factors are related

118
Scatter Diagram

• Getting the most
• Data stratification may be required because of
  intervening factors and changing patterns in the
  relationship
• The plotted relationship between two factors may
  change direction.

119
Systematic Diagram

• What is it?
• A graphic representation of the different levels
  of actions needed to achieve a goal
• A management tool used to generate specific
  action items that can be implemented to
  accomplish a broad goal

120
Systematic Diagram

• When is it used?
• Answer yes to all of the following
• 1. Has a broad task or goal become the
• focus of the teams work?
• 2. Is the action plan to accomplish the goal
• or task likely to be complex?

121
Systematic Diagram

• How is it made?
• 1. Record the problem or goal statement.
• 2. Generate the first level of items.
• 3. Complete the systematic diagram under
• each major path.
• 4. Study the diagram.

122
Systematic Diagram

• Remember
• Used to generate a specific list of action items
  which can be implemented to achieve a goal
• Used by a team to
• plan a test for an improvement theory
• plan for standardizing an improvement
• plan for continuous improvement

123
Systematic Diagram

• Getting the most
• Assign responsibility for completion of action
  items when diagram is completed

124
X-R Chart

• What is it?
• A picture of system data gathered over time
• A chart that shows how the mean and range of the
  subgroups change over time
• A tool to help minimize the chance of overcontrol
  or undercontrol

125
X-R Chart

• When is it used?
• Answer yes to all of the following
• 1. Do you need to assess the stability of a
  system?
• 2. Is data in variables form?
• 3. Is data collected in subgroups larger than
  one?
• 4. Is the time order of subgroups preserved?

126
X-R Chart

• How is it made?
• Complete the header information.
• Record the data.
• Calculate the statistics for each subgroup.
• Calculate the averages for the subgroup
  statistics.
• Calculate the control limits.
• Determine the scaling for the charts.
• Draw the center line and control limits.
• Plot the values on the charts.
• Interpret the control chart.

127
X-R Chart

• Remember
• Shows how variables data changes over time
• Helps to identify special and common causes of
  variation

128
X-R Chart

• Getting the most
• Assess stability
• Stratify data
• Track system changes as a result of implemented
  improvement theories

129
X-MR Chart

• What is it?
• A picture of system data gathered over time
• A chart that shown how individual measured values
  and the variability between subsequent values
  change over time
• A tool to help minimize the chance of overcontrol
  or undercontrol

130
X-MR Chart

• When is it used?
• Answer yes to all of the following
• 1. Do you need to assess the stability of
• a system.
• 2. Is data in variables form?
• 3. Is data collected in subgroups of one?
• 4. Is the time order of subgroups
• preserved?

131
X-MR Chart

• How is it made?
• 1. Complete the header information.
• 2. Record the data.
• 3. Calculate the moving ranges.
• 4. Calculate the overall averages.
• 5. Calculate the control limits.
• 6. Determine the scaling for the charts.
• 7. Draw the center lines and control limits.
• 8. Plot the values on the charts.
• 9. Interpret the control chart.

132
X-MR Chart

• Remember
• Shows how variables data changes over time
• Helps to identify special and common causes of
  variation
• n 1
• The range is found by comparing subsequent
  subgroups

133
X-MR Chart

• Getting the most
• Assess stability
• Stratify data
• Track system changes as a result of implemented
  improvement theories